A TIME SERIES ANALYSIS OF FOUR MAJOR CRYPTOCURRENCIES

Boris Radovanov, Aleksandra Marcikić, Nebojša Gvozdenović

DOI Number

https://doi.org/10.22190/FUEO1803271R

First page

271

Last page

278

Abstract

Because of increasing interest in cryptocurrency investments, there is a need to quantify their variation over time. Therefore, in this paper we try to answer a few important questions related to a time series of cryptocurrencies. According to our goals and due to market capitalization, here we discuss the daily market price data of four major cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Ripple (XRP) and Litecoin (LTC). In the first phase, we characterize the daily returns of exchange rates versus the U.S. Dollar by assessing the main statistical properties of them. In many ways, the interpretation of these results could be a crucial point in the investment decision making process. In the following phase, we apply an autocorrelation function in order to find repeating patterns or a random walk of daily returns. Also, the lack of literature on the comparison of cryptocurrency price movements refers to the correlation analysis between the aforementioned data series. These findings are an appropriate base for portfolio management. Finally, the paper conducts an analysis of volatility using dynamic volatility models such as GARCH, GJR and EGARCH. The results confirm that volatility is persistent over time and the asymmetry of volatility is small for daily returns.

Kristoufek, L. (2015). What are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis. PLoS ONE 10. Retrieved from: journals.plos.org/plosone/article?id=10.1371/journal.pone.0123923 Accessed on: 9 March 2018.